What statistical method is used to visualize the relationship between two variables?

The most appropriate statistical method to visualize the relationship between two variables is linear regression. Linear regression involves fitting a line through a scatter plot of the data points, allowing you to see how one variable may predict or affect another. This method provides a clear graphical representation of the relationship, highlighting both the trend and the strength of the association between the variables.

By using linear regression, you can analyze the slope and intercept of the fitted line to quantify the relationship, such as determining whether it is positive or negative and how steep that relationship is. This visual representation is particularly useful when assessing how changes in one variable may lead to changes in another, as it helps you identify patterns and make predictions based on the data.

Other methods mentioned have their own purposes: for instance, the mean provides a measure of central tendency, the standard deviation indicates the variability of data, and correlation measures the strength and direction of a relationship between two variables without visualizing it. However, when the goal is specifically to visualize the interaction and trend, linear regression stands out as the most effective method.